%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\subsection{Participatory simulation process}

\subsubsection{Definition}

According to Murakami in \cite{Murakami:2006}, a participatory simulation is a multi-agent simulation in which one or more agents are controlled by humans. The actors can either observe the behavior of agents and correct it if necessary or even fully control them, \emph{i.e.} choose every action it will do. Participatory simulations appear to be a good solution to two key issues in simulation: on the one hand they allow users to be immersed in a simulation to test various scenarios and to have a better view of the simulated system, on the other hand human beings controlling agents provide agents with the best and most possible realistic behavior.


\subsubsection{Steps of a participatory simulation}

Once the model has been implemented, the modeler will choose and invite the participants to take part to the simulation. Each participant is chosen for his specific skills and knowledge, that will permit him to control efficiently some agents. Each participant will thus receive a suitable role. They can initialize the parameters, execute and interact with the simulator and observe the outputs on their personal interface that has been specifically designed for each role.
%
Moreover they will interact and communicate with other participants in order to improve the results of the simulator and/or to get the desired outputs.



%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\subsection{Features for a participatory simulation framework}

In order to build our participatory simulation framework, we need to extract the main features of such a framework. These features will afterwards be used to construct the meta-model.

\subsubsection{The need of a multiple interface}

In complex system researches, most steps of the modeling and simulation activities require, in addition to modelers and computer scientists, experts from various domains (such as agriculture, urban planning, disaster prevention, environment, industrial development \cite{Daniellou:2007} or epidemiology \cite{Amouroux:2010}) who exchange their experiences, knowledge \cite{Guyot:2004} and expertise. Integrating experts in the modeling and simulation loop is essential for the conceptual analysis of the model or for the analysis of the results of the simulation in comparison with real phenomena.
%
To effectively facilitate this integration, participants can be invited to take part to multidisciplinary collaborative experiments. This multidisciplinary is essential to explore individual and collective decision-making \cite{GUYOT:2006}.

However, the mission of each participant must be clear and specific. In other words, each participant has a particular role in the simulation that gives him specific rights during the simulation. In the sequel we will define these rights as the specification of the elements the user can view and control and they will thus define the interface of each stakeholder. This dedicated interface helps the researchers to work on familiar data by keeping only variables and actions corresponding to his expertise domain.


\subsubsection{The need of collaboration}

As shown above, various stakeholders, possibly geographically separated, are needed to interact simultaneously with the simulation.
Nevertheless their interactions around a simulator is one of the key benefits of the participative approach: the common understanding of the situation and the clear awareness of the issues can emerge only thanks to these interactions. Our framework should thus be as collaborative as possible to permit free interactions among participants or group of participants.


\subsubsection{The need of genericity}

At the opposite of existing ad hoc simulators (as the ones presented in introduction) built from scratch for a specific application, simulation platforms (such as Repast \cite{REPAST:2006}, Netlogo \cite{NETLOGO:1999} or GAMA \cite{GAMA:2010}) can be used to ease and accelerate the development of simulators. Such platforms integrate often a simple modeling language (\emph{e.g.} Netlogo and GAMA) or a Java interface for agents which help modelers to develop agents and their behavior. They also handle the kernel of the simulator (in particular the scheduler) and the monitoring of the simulation. They thus offer lot of functionalities that speed up the development of a simulator.
%
Nevertheless they have nothing to develop collaborative and participatory simulations in terms of multiple interface or network ease.
And that is often this point that induces the choice of an ad hoc development.

Taking into account the great number of ad hoc simulators but also the potential benefits that can bring simulation platforms for the development of participatory simulators, we chose that our framework should not be limited to a particular simulator of platform. We thus argue that it should be generic, \emph{i.e.} able to host various ones.

\bigskip
To conclude we argue that our participatory simulation framework should have a multiple interface and be collaborative and generic. This three features have driven the meta-model proposed in the following section. 